Computer-driven route planning applications are utilized every day to aid users in locating points of interest, such as particular buildings, addresses, and the like. Additionally, in several existent commercial applications users can vary a zoom level, thereby enabling variation of context and detail as a zoom level of a map is altered. For example, as a user zooms in on a particular location, details such as names of local roads, identification and location of police and fire stations, identification and location of public services, such as libraries, museums, and the like can be provided to the user. When zooming out, the user can glean information from the map such as location of the point of interest within a city, state, and/or country, proximity of the point of interest to major freeways, proximity of the point of interest to a specific city, and the like. In some applications, satellite images can be utilized to provide users with additional detail regarding a particular geographic location or region. For example, a prospective purchaser of a house can obtain an overhead satellite image of the house, thereby enabling the prospective purchaser to view lines of occupation, proximity of the house to other adjacent houses, and other information that may be pertinent to the user.
Furthermore, conventional computer-implemented mapping applications often include route planning applications that can be utilized to provide users with directions between different locations. Pursuant to an example, a user can provide a route planning application with a beginning point of travel and an end point of travel (e.g., beginning and ending addresses). The route planning application can include or utilize representations of roads and intersections and one or more algorithms to output a suggested route of travel. These algorithms can output routes depending upon user-selected parameters. For instance, a commercial route planning application can include a check-box that enables a user to specify that she wishes to avoid highways. Similarly, a user can inform the route planning application that they wish to travel on a shortest route or a route that takes a least amount of time (as determined by underlying algorithms).
Over the last several years, individuals have grown to increasingly rely on route planning applications to aid them in everything from locating a friend's house to planning cross-country road trips.
In the general case, a set of feasible streets are considered and a search algorithm is used to create a route that optimizes some objective function such as minimizing total distance or time to travel between two points. To perform optimization, a search method is applied to search among and to identify best routes between two or more locations. Search methods include comprehensive combinatorial search, or more efficient methods such as the Dykstra search algorithm, or A* search.
Route planning applications are also no longer confined to desktop computers. Rather, many automobile models are now equipped with standard mapping functionality, wherein the automobiles include graphical displays on a console to provide mapping data and directions to a user. Oftentimes, a compact disk or other storage medium that includes data to enable utilization of route-planning functionality must be purchased and loaded prior to use of the route planning application. As road conditions change, such as speed limits, number of lanes, etc., updates can be provided. Automobiles with GPS functionality (or other location identifying functionality) can additionally include real-time directions, wherein directions are provided to users of the automobile while they travel.
These route planners are fairly reliable in connection with details such as posted speed limits, location of one-way streets, and related information. However, conventional applications that include route-planning functionality make assumptions regarding the state of roads. With more specificity, today's route planning applications are built around assumptions of constancy and universality, such that optimal routes provided by the applications are independent of time of day, day of week, and detailed user preferences. In actuality, however, these assumptions do not hold. For example, in many instances, a best route between two points during rush hour in an urban area is not an optimal route at midnight between the same two points. Conventional route planning applications, however, do not take such context into account when providing routes for users. Similarly, different drivers may prefer different routes between the same two points. For example, one driver may avoid highways or particularly difficult merges, or is willing to extend duration of a journey by a few minutes in order to follow a scenic coastal road, while the other driver simply wants to arrive as quickly as possible or to traverse the shortest distance.